Liquidity providers deposit funds into Metavault.Trade and receive trading fees from traders (supply-side fees).

Metavault.Trade is a non-custodial exchange for spot and perpetual contracts built on Polygon. Metavault.Trade was founded by an anonymous team and was launched in May 2022.

MVX tokenholders own and govern the protocol. They currently take a cut of the total trading fees paid by traders (revenue).

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Metavault.Trade

# Metavault.Trade Average fees per user (AFPU) Methodology

## 1. Overview

Average Fees Per User (AFPU) measures the average daily revenue generated per active user on Metavault.Trade, a derivatives trading platform on Polygon. This metric answers the question "How much revenue does each active trader generate on average per day?" The calculation divides daily total fees by daily active users, providing insight into user monetization efficiency and average transaction value per user.

## 2. Data sources

The AFPU calculation relies on the following raw data sources:

- **Polygon blockchain events**: Parsed event logs from Metavault's Vault contract including `IncreasePosition`, `DecreasePosition`, `Swap`, `CollectMarginFees`, and `CollectSwapFees` events
- **Transaction data**: Polygon transaction records containing block timestamps, transaction hashes, and log indices for event ordering
- **External data**: End-of-day token price feeds for USD conversion and token metadata for decimal place correction
- **Contract metadata**: Metavault Vault contract addresses and event signatures for proper event identification

## 3. Step-by-step calculation

### Component A: Daily active user identification

- **Purpose**: Identifies and counts unique traders who performed any trading activity on each day
- **Logic**: Extracts user addresses from three types of Polygon trading events. From `IncreasePosition` events, captures the `account` parameter representing traders opening or increasing perpetual positions. From `DecreasePosition` events, captures the `account` parameter for traders closing or reducing positions. From `Swap` events, captures the `account` parameter for spot trading activity. All events are filtered to Polygon chain only and classified as derivatives market activity with perpetual business segment. Daily aggregation uses timestamp truncation to day boundaries, grouping by user address to ensure each unique trader is counted once per day regardless of transaction volume.
- **Key fields**: `account` addresses from trading events, `block_timestamp` for daily grouping, `transaction_hash` for event identification

### Component B: Daily fee collection

- **Purpose**: Calculates total fees collected from both perpetual and spot trading activities
- **Logic**: Combines fee data from two distinct sources. From `CollectMarginFees` events, extracts the `feeTokens` parameter representing trading fees collected during leveraged perpetual positions, tagged as "Perpetual trading" business line. From `CollectSwapFees` events, extracts the `feeTokens` parameter for fees from spot trading, tagged as "Spot trading" business line. Both fee types include the `token` parameter identifying the fee token address and amount in raw token units. Daily aggregation sums all fees by day, maintaining separation by business line and token type.
- **Key fields**: `feeTokens` amounts from fee collection events, `token` addresses for token identification, `block_timestamp` for daily grouping

### Component C: User count aggregation

- **Purpose**: Aggregates daily active users across multiple dimensions while preventing double-counting
- **Logic**: Uses HyperLogLog algorithm to deduplicate user addresses across different event types and dimensions. Creates separate breakdowns for project-level totals, chain-level counts, user type categories, and product-level segmentation. The HyperLogLog approach ensures traders who perform multiple transaction types on the same day are counted only once in the final daily active user count. Applies zero-filling strategy to ensure continuous daily metrics even when no trading activity occurs.
- **Key fields**: Deduplicated `user_dau` counts, dimension categorizations for different aggregation levels

### Component D: Fee USD conversion

- **Purpose**: Converts raw token fee amounts to standardized USD values for consistent reporting
- **Logic**: Takes daily fee amounts in various token denominations and converts them to USD using end-of-day price feeds. Applies decimal correction based on token metadata to ensure proper unit conversion from raw blockchain amounts to human-readable values. Combines perpetual and spot fees into unified daily totals. Applies zero-filling for days with no fee activity to maintain consistent time series data.
- **Key fields**: USD-converted `fees` amounts, corrected decimal places, aggregated daily totals

### Final aggregation

- **Combining components**: The final AFPU calculation uses a macro-driven approach that joins daily fee totals with daily active user counts on matching timestamps and dimensional breakdowns
- **Currency conversion**: All fees are converted to USD using end-of-day prices before the ratio calculation to ensure currency consistency
- **Time aggregation**: Both numerator (fees) and denominator (users) use daily timestamp boundaries truncated to day level for proper alignment
- **Final calculation**: AFPU equals daily total fees in USD divided by daily active user count, with null handling for days when no users are active to prevent division by zero errors

*This methodology was automatically generated by Token Terminal's methodology analyzer.*

Metavault.TradeMVX

Average fees per user (AFPU)

Average fees per user (AFPU)

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